It has been a while since I devoted a post to quantum computation. Meanwhile, we had a cozy, almost private, easy-going, and very interesting discussion thread on my previous, March 2014 post (that featured my Simons Institute videotaped lectures (I,II).)

What can we learn from a failure of quantum computers?

Last week we had a workshop on “Quantum computing: achievable reality or unrealistic dream.” This was a joint venture of the American Physics Society and the Racah Institute of Physics here at HUJI, organized by Professor Miron Ya. Amusia, and it featured me and Nadav Katz as the main speakers. Here are the slides of my lecture: What can we learn from a failure of quantum computers.

On the positive side, Greg Kuperberg and I wrote a paper Contagious error sources would need time travel to prevent quantum computation showing that for a large class of correlated noise, (teleportation-based) quantum fault-tolerance works! Greg and I have had a decade-long email discussion (over 2000 emails) regarding quantum computers, and this work grew from our 2009 discussion (about my “smoothed Lindblad evolution” model), and heavily relies on ideas of Manny Knill.

Nadav Katz: Quantum information science – the state of the art

Some years ago, two brilliant experimentalists, Hagai Eisenberg and Nadav Katz, joined the already strong, mainly theoretical, quantum information group here at HUJI. Nadav Katz gave the second lecture in the workshop, and here are the slides of Nadav’s lecture: Quantum information science – the state of the art.

Experimental progress toward stable encoded qubits

Also very much on the positive side, Nadav mentioned a remarkable recent progress by the Martini’s group showing certain encoded states based on 9 physical qubits which are order-of-magnitude (factor 8.4, to be precise,) more stable than the “raw” qubits used for creating them !!

Update: Further comments on a Shtetl-optimized post (especially a comment by Graeme Smith,) help to place the new achievement of the Martinis group within the seven smilestones toward quantum computers from a 2012 Science paper by Schoelkopf and Devoret, originated by David DiVincenzo’s 2000 paper “The physical implementation of quantum computation“. (You can watch these milestone here also .)

The new achievement of having a very robust realization of certain encoded states can be seen as achieving the 3.5 milestone. The difference between the 3.5th milestone and the 4th milestone plays a central role in the seventh post of my 2012-debate with Aram Harrow in connection with a conjecture I made in the first post (“Conjecture 1″). Aram made the point that classical error-correction can lead to very stable encoded qubits in certain states (which is essentially the 3.5 milestone). I gave a formal description of the conjecture, which essentially asserts that the 4th milestone, namely insisting that encoded qubits allows arbitrary superpositions, cannot be reached. As I said many times (see, for example, the discussion in my 2012 Simons Institute videotaped lecture 2), a convincing demonstration of the 4th milestone, namely implementation of quantum error-correction with encoded qubits which are substantially more stable than the raw qubits (and allow arbitrary superposition for the encoded qubit) will disprove my conjectures. Such stable encoded qubits are expected from implementations of distance-5 surface code. So we are 0.5 milestones away :)

I will be impressed to see even a realization of distance-3 (or distance-5) surface code that will give good quality encoded qubits, even if the encoded qubits will have a quality which is somewhat worse than that of the raw qubits used for the encoding. These experiments, including those that were already carried out, also give various other opportunities to test my conjectures.

Peter Shor’s challenge #1 and my predictions from the failure of quantum computation

My lecture on predictions from the failure of QC is based on two lengthy recent comments (first, second) regarding predictions from the failure of quantum computers. On April 2014, Peter Shor challenged me with the following: Continue reading →

Here are links to a videotaped lecture in two parts entitled “why quantum computers cannot work” recorded at the Simons Institute for the Theory of Computing on December 2013 and two additional videos: a short talk on topological quantum computers and a twelve minute overview. Here are the links: Overview, Part I, Part II, Topological QC. (Update, Nov 14: BosonSampling.)

Why Quantum Computers Cannot Work:

Overview and Vision.

Why Quantum Computers Cannot Work I:

From the “Trivial Flow” to Smoothed Lindblad Evolutions

Why Quantum Computers Cannot Work II:

Debate, Reasons to Disbelieve, and Experimentation

Why Topological Quantum Computers Cannot Work

The Geometry of Spacetime is Enabled by the Failure of Quantum Fault-Tolerance

Left: Nick Read; Right The front page of Nick’s 1990 famous paper with Greg Moore on nonabelions, and below his email to me from March 2005 on topological quantum computation. (click for full view.)

Left: the argument regarding topological QC demonstrated via Harris’ famous cartoon. While not strictly needed I expect the argument to extend from qubits to gates as well. Right: a recent discussion with Nick over Shtetl Optimized (click for full view). Update: We are actually not in an agreement as it seems from the above discussion (see the discussion below).

Update (Nov’ 2014): A fifth video, this time in front of a live audience

Complexity and Sensitivity of Noisy BosonSampling

Added later (April 18): Let me quote from what Steve wrote about the videos: The surprising part is the superior production value relative to your typical videotaped lecture (at least for the first overview video). Producing the videos was an interesting and demanding experience and I was certainly happy to read Steve’s description of the production value. (Of course, the main purpose of Steve’s post was to express his disagreement with the content of the videos. See either the post or Co-‘s comment below.)

Also there are two earlier versions of my lecture (in 1-hour format) that were videotaped. The first was taken by Jesus De Loera in Davis. Very interesting shooting-angle and interesting comments by Greg Kuperberg, Bruno Nachtergaele and other participants. The second was taken in Seattle in a UW-PIMS colloquium lecture. Again interesting questions by several participants including James Lee and John Sidles.

(July:) The Simons Institite (almost identical) versions of the movies are now linked from the web-page of my November 15 lecture at SI.

(Added nov 2014): The only difference from the HUJI version is that there are no opening slides and that for the closing slides I used two pictures of my department’s administrative staff.

The administrative crew of the Einstein Institite of Mathematics (click to enlarge)

I thought of it as a nice opportunity to thank our great administrative staff whose part is crucial in the academic endeavor, and this is a good opportunity to thank the staff in my second academic home – Yale University, in the Simons Institute, in many other places.

Alistair Sinclair and the Simons Institure friendly and helpful staff (click for full size)

Following Saharon Shelah: How to watch these videos

(Added Nov 2014)

Saharon Shelah explained in an introduction to one of his books, that instructions on “how to read this book” are actually instruction on “how to not read this book”. If you want to read the book you start on page 1 and read through to the last page. Instructions for “how to read this book” rather tell you how to jump to a place that interests you.

So, in a similar spirit, here are direct links to the different parts of the videos.

Update (Nov 2014): Noise sensitivity of BosonSampling and computational complexity of noisy BosonSampling are studied in this paper by Guy Kindler and me. Some of my predictions from this post turned out to be false. In particular the noisy BosonSampling is not flat and it does depend on the input matrix. However when the noise level is a constant BosonSampling is in P, and when it is above 1 over the number of bosons, we cannot expect robust experimental outcomes.

—–

Following are some preliminary observations connecting BosonSampling, an interesting computational task that quantum computers can perform (that we discussed in this post), and noise-sensitivity in the sense of Benjamini, Schramm, and myself (that we discussed here and here.)

BosonSampling and computational-complexity hierarchy-collapse

Suppose that you start with n bosons each can have m locations. The i-th boson is in superposition and occupies the j-th location with complex weight . The bosons are indistinguishable which makes the weight for a certain occupation pattern proportional to the permanent of a certain n by n submatrix of the n by m matrix of weights.

Boson Sampling is a task that a quantum computer can perform. As a matter of fact, it only requires a “boson machine” which represents only a fragment of quantum computation. A boson machine is a quantum computer which only manipulates indistinguishable bosons with gated described by phaseshifters and beamsplitters.

Since universal quantum computers can achieve BosonSampling (and the other related computational tasks considered by TD and BJS), this is a very strong indication for the computational complexity advantage of quantum computers which arguably brings us with quantum computers to the “cozy neighborhood” of NP-hardness.

Noisy quantum computers with quantum fault-tolerance are also capable of exact BosonSampling and this strong computational-complexity quantum-superiority applies to them as well.

Realistic BosonSampling and Gaussian Permanent Estimation (GPE)

Aaronson an Arkhipov considered the following question that they referred to as Gaussian Permanent Approximation.

Problem (Problem 2 from AA’s paper): (): Given as imput a matrix of i.i.d Gaussians,together with error bounds ε, δ > o, estimate to within additive error with probability at leat 1-δ over X, in time.

They conjectured that such Gaussian Permanent Approximation is computationally hard and showed (Theorem 3) that this would imply that sampling w.r.t. states achievable by boson machines cannot even be approximated by classical computing (unless PH collapses). They regarded questions about approximation more realistic in the context of decoherence where we cannot expect exact sampling.

Scott Aaronson also expressed guarded optimism that even without quantum fault-tolerance BosonSampling can be demonstrated by boson machines for 20-30 bosons, leading to strong experimental evidence for computational advantage of quantum computers (or, if you wish, against the efficient Church-Turing thesis).

Let us consider the following variation that we refer to as Noisy Gaussian Permanent Estimation:

Problem 2′: (): Given as imput a matrix of i.i.d Gaussians, and a parameter t>0 let NPER (M), be the expected value of the permanent for where E=. Given the input matrix M together with error bounds ε, δ > o, estimate NPER(M) to within additive error with probability at leat 1-δ over X, in time.

Problem 2′ seems more relevant for noisy boson machines (without fault-tolerance). The noisy state of the computer is based on every single boson being slightly mixed, and the permanent computation will average these individual mixtures. We can consider the relevant value for t to be a small constant. Can we expect Problem 2′ to be hard?

The answer for Question 2′ is surprising. I expect that even when is very very tiny, namely for , the expected value of NPER(M) (essentially) does not depend at all on M!

Noise Sensitivity a la Benjamini, Kalai and Schramm

Noise sensitivity for the sense described here for Boolean functions was studied in a paper by Benjamini Schramm and me in 1999. (A related notion was studied by Tsirelson and Vershik.) Lectures on noise sensitivity and percolation is a new beautiful monograph by Christophe Garban and Jeff Steif which contains a description of noise sensitivity. The setting extends easily to the Gaussian case. See this paper by Kindler and O’donnell for the Gaussian case. In 2007, Ofer Zeituni and I studied the noise sensitivity in the Gaussian model of the maximal eigenvalue of random Gaussian matrices (but did not write it up).

Noise sensitivity depends on the degree of the support of the Fourier expansion. For determinants or permanents of an n by n matrices the basic formulas as sums of generalized diagonals describe the Fourier expansion, so the Fourier coefficients are supported on degree-n monomials. This implies that the determinant and the permanent are very noise sensitive.

Noisy Gaussian Permanent Estimation is easy

Noisy Gaussian Permanent Estimation is easy, even for very small amount of noise, because the outcome does not depend at all on the input. It is an interesting question what is the hardness of NGPE is when the noise is below the level of noise sensitivity.

Update (March, 2014) Exploring the connection between BosonSampling and BKS-noise sensitivity shows that the picture drawn here is incorrect. Indeed, the square of the permanent is not noise stable even when the noise is fairly small and this shows that the noisy distribution does not approximate the noiseless distribution. However the noisy distribution does depend on the input!

AA’s protocol and experimental BosonSampling

Scott and Alex proposed a simple experiment described as follows : “An important motivation for our results is that they immediately suggest a linear-optics experiment, which would use simple optical elements (beamsplitters and phaseshifters) to induce a Haar-random unitary transformation U on an input state of n photons, and would then check that the probabilities of various final states of the photons correspond to the permanents of submatrices, as predicted by quantum mechanics.”

Recently, four groups carried out interesting BosonSampling experiments with 3 bosons (thus for permanents of 3 by 3 matrices.) (See this post on Scott’s blog.)

BKS-noise sensitivity is giving simple predictions on how things will behave as a function of the number of bosons and this can be tested even with experiments with very small number of bosons. When you increase the number of bosons the distribution will quickly become uniform for the various final states. The correlation between the probabilities and the value corresponding to permanents will rapidly go to zero.

Some follow-up questions

Here are a few interesting questions that deserve further study.

1) Does problem 2′ capture the general behavior of noisy boson machines? To what generality noise sensitivity applies for general functions described by Boson sampling distributions?

(There are several versions for photons-based quantum computers including even an important model by Knill, Laflamme, and Milburn that support universal quantum computation. The relevance of BKS noise-sensitivity should be explored carefully for the various versions.)

2) Is the connection with noise sensitivity relevant to the possibility to have boson machines with fault tolerance?

3) What is the Gaussian-quantum analog for BKS’s theorem asserting that noise sensitivity is the law unless we have substantial correlation with the majority function?

4) What can be said about noise-sensitivity of measurements for other quantum codes?

A few more remarks:

More regarding noisy boson machines and quantum fault tolerance

Noisy boson machines and BosonSampling are related to various other issues regarding quantum fault-tolerance. See my added recent remarks (about the issue of synchronization, and possible modeling using smoothed Lindblad evolutions) to my old post on AA’s work.

Noise sensitivity and the special role of the majority function

The main result of Itai, Oded, and me was that a Boolean function which is not noise sensitive must have a substantial correlation with the majority function. Noise sensitivity and the special role of majority for it gave me some motivation to look at quantum fault-tolerance in 2005 (see also this post,) and this is briefly discussed in my first paper on the subject, but until now I didn’t find an actual connection between quantum fault-tolerance and BKS-noise-sensitivity.

Censorship

It is an interesting question which bosonic states are realistic, and it came up in some of my papers and in the discussion with Aram Harrow and Steve Flammia (and their paper on my “Conjecture C”).

A sort of conclusion

BosonSampling was offered as a way to prove that quantum mechanics allows a computational advantage without using the computational advantage for actual algorithmic purpose. If you wish, the AA’s protocol is offered as a sort of zero-knowledge proof that the efficient Church-Turing thesis is false. It is a beautiful idea that attracted interest and good subsequent work from theoreticians and experimentalists. If the ideas described here are correct, BosonSampling and boson machines may give a clear understanding based on BKS noise-sensitivity for why quantum mechanics does not offer computational superiority (at least not without the magic of quantum fault-tolerance).

Avi’s joke and common sense

Here is a quote from AA referring to a joke by Avi Wigderson: “Besides bosons, the other basic particles in the universe are fermions; these include matter particles such as quarks and electrons. Remarkably, the amplitudes for n-fermion processes are given not by permanents but by determinants of n×n matrices. Despite the similarity of their definitions, it is well-known that the permanent and determinant differ dramatically in their computational properties; the former is #P-complete while the latter is in P. In a lecture in 2000, Wigderson called attention to this striking connection between the boson and fermion dichotomy of physics and the permanent-determinant dichotomy of computer science. He joked that, between bosons and fermions, ‘the bosons got the harder job.’ One could view this paper as a formalization of Wigderson’s joke.”

While sharing the admiration to Avi in general and Avi’s jokes in particular, if we do want to take Avi’s joke seriously (as we always should), then the common-sense approach would be first to try to understand why is it that nature treats bosons and fermions quite equally and the dramatic computational distinction is not manifested at all. The answer is that a crucial ingredient for a computational model is the modeling of noise/errors, and that noise-sensitivity makes bosons and fermions quite similar physically and computationally.

Eigenvalues, determinants, and Yuval Filmus

It is an interesting question (that I asked over Mathoverflow) to understand the Fourier expansion of the set of eigenvalues, the maximum eigenvalue and related functions. At a later point, last May, I was curious about the Fourier expansion of the determinant, and for the Boolean case I noticed remarkable properties of its Fourier expansion. So I decided to ask Yuval Filmus about it:

Dear Yuval

I am curious about the following. Let D be the function defined on {-1,1}^n^2

which associates to every +1/1 matrix its determinant.

What can be said about the Fourier transform of D? It looks to me that easy arguments shows that the Fourier transform is supported only on subsets of the entries

so that in every raw and columns there are odd number of entries. Likely there are even further restrictions that I would be interested to explore.

Do you know anything about it?

best Gil

Yuval’s answer came a couple of hours later like a cold shower:

Hi Gil,

The determinant is a sum of products of generalized diagonals.

Each generalized diagonal is just a Fourier character, and they are all different.

In other words, the usual formula for the determinant *is* its Fourier transform

This reminded me of a lovely story of how I introduced Moni Naor to himself that I should tell sometime.

What else can a quantum computer sample?

The ability of quantum computers to sample (exactly) random complex Gaussian matrices according to the value of their permanents is truly amazing! If you are not too impressed by efficient factoring but still do not believe that QC can reach the neighborhood of NP-hard problems you may find this possibility too good to be true.

I am curious if sharp P reductions give us further results of this nature. For example, can a QC sample random 3-SAT formulas (by a uniform distribution or by a certain other distribution coming from sharp-P reductions) according to the number of their satisfying assignments?

Can QC sample integer polytopes by their volume or by the number of integer points in them? Graphs by the number of 4-colorings?

Update (July 2013): QStart was a very nice event- there were many interesting talks, and the speakers made the effort to have lectures accessible to the wide audience while discussing the cutting edge and at times technical matters.Streaming video of the talks is now available.

This is the third and last post giving a timeline and some non technical highlights from my debate with Aram Harrow.

Where were we

After Aram Harrow and I got in touch in June 2011, and decided to have a blog debate towards the end of 2011, the first post in our debate describing my point of view was launched on January, 2012 and was followed by three posts by Aram. The discussion was intensive and interesting. Here is a link to my 2011 paper that initiated the debate and to a recent post-debate presentation at MIT.

Happy passover, readers!

Back to the debate: Conjecture C is shot down!

In addition to his three posts, Aram and Steve Flammia wrote a paper refuting one of my Conjectures (Conjecture C). We decided to devote a post to this conjecture.

Quantum refutations and reproofs

The first version of the post started with this heartbreaking eulogy for Conjecture C. At the end most of it was cut away. But the part about Aram’s grandchildren was left in the post.

Eulogy for Conjecture C

(Gil; old version:) When Aram wrote to me, inn June 2011, and expressed willingness to publicly discuss my paper, my first reaction was to decline and propose having just private discussions. Even without knowing Aram’s superb track record in debates, I knew that I put my beloved conjectures on the line. Some of them, perhaps even all of them, will not last. Later, last December, I changed my mind and Aram and I started planning our debate. My conjectures and I were fully aware of the risks. And it was Conjecture C that did not make it.

A few words about Conjecture C

Conjecture C, while rooted in quantum computers skepticism, was a uniter and not a divider! It expressed our united aim to find a dividing line between the pre- and post- universal quantum computer eras.

Aram’s grandchildren and the world before quantum computers

When Aram’s grandchildren will ask him: “Grandpa, how was the world before quantum computers?” he could have replied: “I hardly remember, but thanks to Gil we have some conjectures recording the old days, and then he will state to the grandchildren Conjectures 1-4 and the clear dividing line in terms of Conjecture C, and the grandchildren will burst in laughter about the old days of difficult entanglements.” Continue reading →

This is the second of three posts giving few of the non-technical highlights of my debate with Aram Harrow. (part I)

After Aram Harrow and I got in touch in June 2011, and decided to have a blog debate about quantum fault-tolerance towards the end of 2011, the first post in our debate was launched on January 30, 2012. The first post mainly presented my point of view and it led to lovely intensive discussions. It was time for Aram’s reply and some people started to lose their patience.

(rrtucky) Is Aram, the other “debater”, writing a dissertation in Greek, as a reply?

Flying machines of the 21st century

(Aram) There are many reasons why quantum computers may never be built… The one thing I am confident of is that we are unlikely to find any obstacle in principle to building a quantum computer.

(Aram) If you want to prove that 3-SAT requires exponential time, then you need an argument that somehow doesn’t apply to 2-SAT or XOR-SAT. If you want to prove that the permanent requires super-polynomial circuits, you need an argument that doesn’t apply to the determinant. And if you want to disprove fault-tolerant quantum computing, you need an argument that doesn’t also refute fault-tolerant classical computing.

From the discussion

Why not yet? Boaz set a deadline

(Boaz Barak) could [you] explain a bit about the reasons why people haven’t been able to build quantum computers with more than a handful of qubits yet? Continue reading →

How the debate came about

(Email from Aram Harrow, June 4, 2011) Dear Gil Kalai, I am a quantum computing researcher, and was wondering about a few points in your paper…

(Aram’s email was detailed and thoughtful and at the end he proposed to continue the discussion privately or as part of a public discussion.)

(Gil to Aram) Thank you for your email and interest. Let me try to answer the points you raised. … (I gave a detailed answer.) … Right now, I don’t plan on initiating a public discussion. How useful such public discussions are (and how to make them useful) is also an interesting issue. Still they were useful for me, as two of my conjectures were raised first in a discussion on Dave Bacon’s blog and another one is partially motivated by a little discussion with Peter Shor on my blog. Continue reading →